With the increasing popularity of mobile devices, including cellphone devices, handheld devices, handheld computers, smartphones, PDAs, etc., there is a need for improving the user interface experience by increasing user text input speed, reducing text entry errors, and improving the overall user experience.
Mobile devices with capacitive or resistive touch capabilities often utilize a touch screen keyboard, a hardware keyboard, speech recognition, handwriting recognition, or combination of the four, for entry of text input. Touch screen keyboards enable larger displays for videos, web pages, email, etc., without the requirement of a physical keyboard. Because touch screen keyboards are software-based, they can be easily adjusted for different languages, touch screen orientation, and key layouts. Furthermore, touch screen keyboards can be augmented with widgets for word prediction and disambiguation candidates.
Users of devices with touch screens, especially mobile devices, have varying abilities and styles of entering text. A particular user may tend to use certain words, including words not found in a system dictionary, more or less frequently depending on the input scope. For example, the frequency of word usage used may vary depending on whether the input scope is a message body, subject lines, or to/from fields. Similarly, the frequency of word usage or typing accuracy may also vary between individual users. Therefore, there exists ample opportunity for improvement in technologies related to facilitating user input on electronic devices by learning user tendencies when entering text in order to accelerate user text entry and reduce user input error rates while taking into account input scope and the completion state of a given text entry.